autotrain-radesky-lab-span-v1

datasaur-dev/autotrain-radesky-lab-span-v1

autotrain-radesky-lab-span-v1 is a token classification model from datasaur-dev. Use it when you need labels on individual words, such as names. It is set up for transformers. The card lists the license as apache-2.0.

should probably proofread and complete it, then remove this comment. --

Downloads · 30 days

23% of all-time downloads

All-time downloads

Public

Parameters

109M

10.9 GB on disk

Likes

Public

Hugging Face

Repo makeup

Click a slice to open those files.

.safetensors436 MB · 100%

At a glance

Task: Token Classification
Library: transformers
License: apache-2.0
Model type: bert
Access: Public
Created: Mar 10, 2025
Updated: Mar 10, 2025
SHA: e0aa77ef

Try a prompt

Base models

Datasets

datasaur-dev/datasaur-MTFiZjUwM2Q-ZWJiZDRmNGI

Model card

From the Hugging Face model README

autotrain-radesky-lab-span-v1

This model is a fine-tuned version of bert-base-uncased on the datasaur-dev/datasaur-MTFiZjUwM2Q-ZWJiZDRmNGI dataset. It achieves the following results on the evaluation set:

Loss: 0.2518
Precision: 0.7854
Recall: 0.8385
F1: 0.8111
Accuracy: 0.9710

Model description

More information needed

Intended uses & limitations

More information needed

Training and evaluation data

More information needed

Training procedure

Training hyperparameters

The following hyperparameters were used during training:

learning_rate: 0.0001
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 25

Training results

Training Loss	Epoch	Step	Validation Loss	Precision	Recall	F1	Accuracy
No log	1.0	455	0.2565	0.5114	0.4688	0.4891	0.9440
0.2875	2.0	910	0.3292	0.2957	0.2865	0.2910	0.9238
0.1173	3.0	1365	0.1931	0.4347	0.7448	0.5489	0.9531
0.0945	4.0	1820	0.1780	0.5147	0.7292	0.6034	0.9578
0.0559	5.0	2275	0.1924	0.5496	0.75	0.6344	0.9592
0.0412	6.0	2730	0.1673	0.6637	0.7708	0.7133	0.9654
0.0309	7.0	3185	0.1928	0.64	0.75	0.6906	0.9635
0.0231	8.0	3640	0.1938	0.6332	0.7552	0.6888	0.9643
0.0191	9.0	4095	0.1856	0.6667	0.7812	0.7194	0.9670
0.018	10.0	4550	0.2042	0.6610	0.8125	0.7290	0.9659
0.0138	11.0	5005	0.2254	0.6245	0.7969	0.7002	0.9649
0.0138	12.0	5460	0.2193	0.7318	0.8385	0.7816	0.9693
0.0104	13.0	5915	0.2287	0.6568	0.8073	0.7243	0.9643
0.0088	14.0	6370	0.2258	0.6943	0.8281	0.7553	0.9683
0.0052	15.0	6825	0.2323	0.7537	0.7969	0.7747	0.9677
0.0091	16.0	7280	0.2226	0.7067	0.8281	0.7626	0.9678
0.0039	17.0	7735	0.2152	0.7393	0.8125	0.7742	0.9696
0.006	18.0	8190	0.2687	0.7340	0.7760	0.7544	0.9672
0.0024	19.0	8645	0.2464	0.7358	0.8125	0.7723	0.9690
0.0004	20.0	9100	0.2463	0.7583	0.8333	0.7940	0.9694
0.0003	21.0	9555	0.2466	0.7805	0.8333	0.8060	0.9700
0.001	22.0	10010	0.2514	0.7822	0.8229	0.8020	0.9706
0.001	23.0	10465	0.2518	0.7854	0.8385	0.8111	0.9710
0.0002	24.0	10920	0.2586	0.7833	0.8281	0.8051	0.9705
0.0002	25.0	11375	0.2650	0.7681	0.8281	0.7970	0.9697

Framework versions

Transformers 4.48.0
Pytorch 2.5.1+cu124
Datasets 2.20.0
Tokenizers 0.21.0

Task: Token Classification
Library: transformers
Type: bert
License: apache-2.0
Created: Mar 10, 2025
Updated: Mar 10, 2025